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# Copyright Cartopy Contributors
#
# This file is part of Cartopy and is released under the LGPL license.
# See COPYING and COPYING.LESSER in the root of the repository for full
# licensing details.
from __future__ import (absolute_import, division, print_function)
import operator
import warnings
import matplotlib
import matplotlib.collections as mcollections
import matplotlib.ticker as mticker
import matplotlib.transforms as mtrans
import matplotlib.path as mpath
import numpy as np
import shapely.geometry as sgeom
import cartopy
from cartopy.crs import Projection, _RectangularProjection
from cartopy.mpl.ticker import (
LongitudeLocator, LatitudeLocator,
LongitudeFormatter, LatitudeFormatter)
degree_locator = mticker.MaxNLocator(nbins=9, steps=[1, 1.5, 1.8, 2, 3, 6, 10])
classic_locator = mticker.MaxNLocator(nbins=9)
classic_formatter = mticker.ScalarFormatter
_DEGREE_SYMBOL = u'\u00B0'
_X_INLINE_PROJS = (
cartopy.crs.InterruptedGoodeHomolosine,
cartopy.crs.LambertConformal,
cartopy.crs.Mollweide,
cartopy.crs.Sinusoidal,
cartopy.crs.RotatedPole,
)
_POLAR_PROJS = (
cartopy.crs.NorthPolarStereo,
cartopy.crs.SouthPolarStereo,
cartopy.crs.Stereographic
)
def _fix_lons(lons):
"""
Fix the given longitudes into the range ``[-180, 180]``.
"""
lons = np.array(lons, copy=False, ndmin=1)
fixed_lons = ((lons + 180) % 360) - 180
# Make the positive 180s positive again.
fixed_lons[(fixed_lons == -180) & (lons > 0)] *= -1
return fixed_lons
def _lon_hemisphere(longitude):
"""Return the hemisphere (E, W or '' for 0) for the given longitude."""
longitude = _fix_lons(longitude)
if longitude > 0:
hemisphere = 'E'
elif longitude < 0:
hemisphere = 'W'
else:
hemisphere = ''
return hemisphere
def _lat_hemisphere(latitude):
"""Return the hemisphere (N, S or '' for 0) for the given latitude."""
if latitude > 0:
hemisphere = 'N'
elif latitude < 0:
hemisphere = 'S'
else:
hemisphere = ''
return hemisphere
def _east_west_formatted(longitude, num_format='g'):
fmt_string = u'{longitude:{num_format}}{degree}{hemisphere}'
return fmt_string.format(longitude=abs(longitude), num_format=num_format,
hemisphere=_lon_hemisphere(longitude),
degree=_DEGREE_SYMBOL)
def _north_south_formatted(latitude, num_format='g'):
fmt_string = u'{latitude:{num_format}}{degree}{hemisphere}'
return fmt_string.format(latitude=abs(latitude), num_format=num_format,
hemisphere=_lat_hemisphere(latitude),
degree=_DEGREE_SYMBOL)
#: A formatter which turns longitude values into nice longitudes such as 110W
LONGITUDE_FORMATTER = mticker.FuncFormatter(lambda v, pos:
_east_west_formatted(v))
#: A formatter which turns longitude values into nice longitudes such as 45S
LATITUDE_FORMATTER = mticker.FuncFormatter(lambda v, pos:
_north_south_formatted(v))
class Gridliner(object):
# NOTE: In future, one of these objects will be add-able to a GeoAxes (and
# maybe even a plain old mpl axes) and it will call the "_draw_gridliner"
# method on draw. This will enable automatic gridline resolution
# determination on zoom/pan.
def __init__(self, axes, crs, draw_labels=False, xlocator=None,
ylocator=None, collection_kwargs=None,
xformatter=None, yformatter=None, dms=False,
x_inline=None, y_inline=None, auto_inline=True):
"""
Object used by :meth:`cartopy.mpl.geoaxes.GeoAxes.gridlines`
to add gridlines and tick labels to a map.
Parameters
----------
axes
The :class:`cartopy.mpl.geoaxes.GeoAxes` object to be drawn on.
crs
The :class:`cartopy.crs.CRS` defining the coordinate system that
the gridlines are drawn in.
draw_labels: optional
Toggle whether to draw labels. For finer control, attributes of
:class:`Gridliner` may be modified individually. Defaults to False.
xlocator: optional
A :class:`matplotlib.ticker.Locator` instance which will be used
to determine the locations of the gridlines in the x-coordinate of
the given CRS. Defaults to None, which implies automatic locating
of the gridlines.
ylocator: optional
A :class:`matplotlib.ticker.Locator` instance which will be used
to determine the locations of the gridlines in the y-coordinate of
the given CRS. Defaults to None, which implies automatic locating
of the gridlines.
xformatter: optional
A :class:`matplotlib.ticker.Formatter` instance to format labels
for x-coordinate gridlines. It defaults to None, which implies the
use of a :class:`cartopy.mpl.ticker.LongitudeFormatter` initiated
with the ``dms`` argument, if the crs is of
:class:`~cartopy.crs.PlateCarree` type.
yformatter: optional
A :class:`matplotlib.ticker.Formatter` instance to format labels
for y-coordinate gridlines. It defaults to None, which implies the
use of a :class:`cartopy.mpl.ticker.LatitudeFormatter` initiated
with the ``dms`` argument, if the crs is of
:class:`~cartopy.crs.PlateCarree` type.
collection_kwargs: optional
Dictionary controlling line properties, passed to
:class:`matplotlib.collections.Collection`. Defaults to None.
dms: bool
When default locators and formatters are used,
ticks are able to stop on minutes and seconds if minutes
is set to True, and not fraction of degrees.
x_inline: optional
Toggle whether the x labels drawn should be inline.
y_inline: optional
Toggle whether the y labels drawn should be inline.
auto_inline: optional
Set x_inline and y_inline automatically based on projection.
Notes
-----
The "x" and "y" labels for locators and formatters do not necessarily
correspond to X and Y, but to the first and second coordinates of the
specified CRS. For the common case of PlateCarree gridlines, these
correspond to longitudes and latitudes. Depending on the projection
used for the map, meridians and parallels can cross both the X axis and
the Y axis.
"""
self.axes = axes
#: The :class:`~matplotlib.ticker.Locator` to use for the x
#: gridlines and labels.
if xlocator is not None:
if not isinstance(xlocator, mticker.Locator):
xlocator = mticker.FixedLocator(xlocator)
self.xlocator = xlocator
elif isinstance(crs, cartopy.crs.PlateCarree):
self.xlocator = LongitudeLocator(dms=dms)
else:
self.xlocator = classic_locator
#: The :class:`~matplotlib.ticker.Locator` to use for the y
#: gridlines and labels.
if ylocator is not None:
if not isinstance(ylocator, mticker.Locator):
ylocator = mticker.FixedLocator(ylocator)
self.ylocator = ylocator
elif isinstance(crs, cartopy.crs.PlateCarree):
self.ylocator = LatitudeLocator(dms=dms)
else:
self.ylocator = classic_locator
if xformatter is None:
if isinstance(crs, cartopy.crs.PlateCarree):
xformatter = LongitudeFormatter(dms=dms)
else:
xformatter = classic_formatter()
#: The :class:`~matplotlib.ticker.Formatter` to use for the lon labels.
self.xformatter = xformatter
if yformatter is None:
if isinstance(crs, cartopy.crs.PlateCarree):
yformatter = LatitudeFormatter(dms=dms)
else:
yformatter = classic_formatter()
#: The :class:`~matplotlib.ticker.Formatter` to use for the lat labels.
self.yformatter = yformatter
#: Whether to draw labels on the top of the map.
self.top_labels = draw_labels
#: Whether to draw labels on the bottom of the map.
self.bottom_labels = draw_labels
#: Whether to draw labels on the left hand side of the map.
self.left_labels = draw_labels
#: Whether to draw labels on the right hand side of the map.
self.right_labels = draw_labels
if auto_inline:
if isinstance(self.axes.projection, _X_INLINE_PROJS):
self.x_inline = True
self.y_inline = False
elif isinstance(self.axes.projection, _POLAR_PROJS):
self.x_inline = False
self.y_inline = True
else:
self.x_inline = False
self.y_inline = False
# overwrite auto_inline if necessary
if x_inline is not None:
#: Whether to draw x labels inline
self.x_inline = x_inline
elif not auto_inline:
self.x_inline = False
if y_inline is not None:
#: Whether to draw y labels inline
self.y_inline = y_inline
elif not auto_inline:
self.y_inline = False
#: Whether to draw the x gridlines.
self.xlines = True
#: Whether to draw the y gridlines.
self.ylines = True
#: A dictionary passed through to ``ax.text`` on x label creation
#: for styling of the text labels.
self.xlabel_style = {}
#: A dictionary passed through to ``ax.text`` on y label creation
#: for styling of the text labels.
self.ylabel_style = {}
#: The padding from the map edge to the x labels in points.
self.xpadding = 5
#: The padding from the map edge to the y labels in points.
self.ypadding = 5
#: Allow the rotation of labels.
self.rotate_labels = True
# Current transform
self.crs = crs
# if the user specifies tick labels at this point, check if they can
# be drawn. The same check will take place at draw time in case
# public attributes are changed after instantiation.
if draw_labels and not (x_inline or y_inline or auto_inline):
self._assert_can_draw_ticks()
#: The number of interpolation points which are used to draw the
#: gridlines.
self.n_steps = 100
#: A dictionary passed through to
#: ``matplotlib.collections.LineCollection`` on grid line creation.
self.collection_kwargs = collection_kwargs
#: The x gridlines which were created at draw time.
self.xline_artists = []
#: The y gridlines which were created at draw time.
self.yline_artists = []
# Plotted status
self._plotted = False
# Check visibility of labels at each draw event
# (or once drawn, only at resize event ?)
self.axes.figure.canvas.mpl_connect('draw_event', self._draw_event)
@property
def xlabels_top(self):
warnings.warn('The .xlabels_top attribute is deprecated. Please '
'use .top_labels to toggle visibility instead.')
return self.top_labels
@xlabels_top.setter
def xlabels_top(self, value):
warnings.warn('The .xlabels_top attribute is deprecated. Please '
'use .top_labels to toggle visibility instead.')
self.top_labels = value
@property
def xlabels_bottom(self):
warnings.warn('The .xlabels_bottom attribute is deprecated. Please '
'use .bottom_labels to toggle visibility instead.')
return self.bottom_labels
@xlabels_bottom.setter
def xlabels_bottom(self, value):
warnings.warn('The .xlabels_bottom attribute is deprecated. Please '
'use .bottom_labels to toggle visibility instead.')
self.bottom_labels = value
@property
def ylabels_left(self):
warnings.warn('The .ylabels_left attribute is deprecated. Please '
'use .left_labels to toggle visibility instead.')
return self.left_labels
@ylabels_left.setter
def ylabels_left(self, value):
warnings.warn('The .ylabels_left attribute is deprecated. Please '
'use .left_labels to toggle visibility instead.')
self.left_labels = value
@property
def ylabels_right(self):
warnings.warn('The .ylabels_right attribute is deprecated. Please '
'use .right_labels to toggle visibility instead.')
return self.right_labels
@ylabels_right.setter
def ylabels_right(self, value):
warnings.warn('The .ylabels_right attribute is deprecated. Please '
'use .right_labels to toggle visibility instead.')
self.right_labels = value
def _draw_event(self, event):
if self.has_labels():
self._update_labels_visibility(event.renderer)
def has_labels(self):
return hasattr(self, '_labels') and self._labels
@property
def label_artists(self):
if self.has_labels():
return self._labels
return []
def _crs_transform(self):
"""
Get the drawing transform for our gridlines.
Note
----
The drawing transform depends on the transform of our 'axes', so
it may change dynamically.
"""
transform = self.crs
if not isinstance(transform, mtrans.Transform):
transform = transform._as_mpl_transform(self.axes)
return transform
@staticmethod
def _round(x, base=5):
if np.isnan(base):
base = 5
return int(base * round(float(x) / base))
def _find_midpoints(self, lim, ticks):
# Find the center point between each lat gridline.
if len(ticks) > 1:
cent = np.diff(ticks).mean() / 2
else:
cent = np.nan
if isinstance(self.axes.projection, _POLAR_PROJS):
lq = 90
uq = 90
else:
lq = 25
uq = 75
midpoints = (self._round(np.percentile(lim, lq), cent),
self._round(np.percentile(lim, uq), cent))
return midpoints
def _draw_gridliner(self, nx=None, ny=None, renderer=None):
"""Create Artists for all visible elements and add to our Axes."""
# Check status
if self._plotted:
return
self._plotted = True
# Inits
lon_lim, lat_lim = self._axes_domain(nx=nx, ny=ny)
transform = self._crs_transform()
rc_params = matplotlib.rcParams
n_steps = self.n_steps
crs = self.crs
# Get nice ticks within crs domain
lon_ticks = self.xlocator.tick_values(lon_lim[0], lon_lim[1])
lat_ticks = self.ylocator.tick_values(lat_lim[0], lat_lim[1])
lon_ticks = [value for value in lon_ticks
if value >= max(lon_lim[0], crs.x_limits[0]) and
value <= min(lon_lim[1], crs.x_limits[1])]
lat_ticks = [value for value in lat_ticks
if value >= max(lat_lim[0], crs.y_limits[0]) and
value <= min(lat_lim[1], crs.y_limits[1])]
#####################
# Gridlines drawing #
#####################
collection_kwargs = self.collection_kwargs
if collection_kwargs is None:
collection_kwargs = {}
collection_kwargs = collection_kwargs.copy()
collection_kwargs['transform'] = transform
# XXX doesn't gracefully handle lw vs linewidth aliases...
collection_kwargs.setdefault('color', rc_params['grid.color'])
collection_kwargs.setdefault('linestyle', rc_params['grid.linestyle'])
collection_kwargs.setdefault('linewidth', rc_params['grid.linewidth'])
# Meridians
lat_min, lat_max = lat_lim
if lat_ticks:
lat_min = min(lat_min, min(lat_ticks))
lat_max = max(lat_max, max(lat_ticks))
lon_lines = np.empty((len(lon_ticks), n_steps, 2))
lon_lines[:, :, 0] = np.array(lon_ticks)[:, np.newaxis]
lon_lines[:, :, 1] = np.linspace(lat_min, lat_max,
n_steps)[np.newaxis, :]
if self.xlines:
nx = len(lon_lines) + 1
# XXX this bit is cartopy specific. (for circular longitudes)
# Purpose: omit plotting the last x line,
# as it may overlap the first.
if (isinstance(crs, Projection) and
isinstance(crs, _RectangularProjection) and
abs(np.diff(lon_lim)) == abs(np.diff(crs.x_limits))):
nx -= 1
lon_lc = mcollections.LineCollection(lon_lines,
**collection_kwargs)
self.xline_artists.append(lon_lc)
self.axes.add_collection(lon_lc, autolim=False)
# Parallels
lon_min, lon_max = lon_lim
if lon_ticks:
lon_min = min(lon_min, min(lon_ticks))
lon_max = max(lon_max, max(lon_ticks))
lat_lines = np.empty((len(lat_ticks), n_steps, 2))
lat_lines[:, :, 0] = np.linspace(lon_min, lon_max,
n_steps)[np.newaxis, :]
lat_lines[:, :, 1] = np.array(lat_ticks)[:, np.newaxis]
if self.ylines:
lat_lc = mcollections.LineCollection(lat_lines,
**collection_kwargs)
self.yline_artists.append(lat_lc)
self.axes.add_collection(lat_lc, autolim=False)
#################
# Label drawing #
#################
self.bottom_label_artists = []
self.top_label_artists = []
self.left_label_artists = []
self.right_label_artists = []
if not (self.left_labels or self.right_labels or
self.bottom_labels or self.top_labels):
return
self._assert_can_draw_ticks()
# Get the real map boundaries
map_boundary_vertices = self.axes.patch.get_path().vertices
map_boundary = sgeom.Polygon(map_boundary_vertices)
self._labels = []
if self.x_inline:
y_midpoints = self._find_midpoints(lat_lim, lat_ticks)
if self.y_inline:
x_midpoints = self._find_midpoints(lon_lim, lon_ticks)
for lonlat, lines, line_ticks, formatter, label_style in (
('lon', lon_lines, lon_ticks,
self.xformatter, self.xlabel_style),
('lat', lat_lines, lat_ticks,
self.yformatter, self.ylabel_style)):
formatter.set_locs(line_ticks)
for line, tick_value in zip(lines, line_ticks):
# Intersection of line with map boundary
line = self.axes.projection.transform_points(
crs, line[:, 0], line[:, 1])[:, :2]
infs = np.isinf(line).any(axis=1)
line = line.compress(~infs, axis=0)
if line.size == 0:
continue
line = sgeom.LineString(line)
if line.intersects(map_boundary):
intersection = line.intersection(map_boundary)
del line
if intersection.is_empty:
continue
if isinstance(intersection, sgeom.MultiPoint):
if len(intersection) < 2:
continue
tails = [[(pt.x, pt.y) for pt in intersection[:2]]]
heads = [[(pt.x, pt.y)
for pt in intersection[-1:-3:-1]]]
elif isinstance(intersection, (sgeom.LineString,
sgeom.MultiLineString)):
if isinstance(intersection, sgeom.LineString):
intersection = [intersection]
elif len(intersection) > 4:
# Gridline and map boundary are parallel
# and they intersect themselves too much
# it results in a multiline string
# that must be converted to a single linestring.
# This is an empirical workaround for a problem
# that can probably be solved in a cleaner way.
xy = np.append(intersection[0], intersection[-1],
axis=0)
intersection = [sgeom.LineString(xy)]
tails = []
heads = []
for inter in intersection:
if len(inter.coords) < 2:
continue
tails.append(inter.coords[:2])
heads.append(inter.coords[-1:-3:-1])
if not tails:
continue
elif isinstance(intersection,
sgeom.collection.GeometryCollection):
# This is a collection of Point and LineString that
# represent the same gridline.
# We only consider the first geometries, merge their
# coordinates and keep first two points to get only one
# tail ...
xy = []
for geom in intersection.geoms:
for coord in geom.coords:
xy.append(coord)
if len(xy) == 2:
break
if len(xy) == 2:
break
tails = [xy]
# ... and the last geometries, merge their coordinates
# and keep last two points to get only one head.
xy = []
for geom in reversed(intersection.geoms):
for coord in reversed(geom.coords):
xy.append(coord)
if len(xy) == 2:
break
if len(xy) == 2:
break
heads = [xy]
else:
warnings.warn(
'Unsupported intersection geometry for gridline '
'labels: ' + intersection.__class__.__name__)
continue
del intersection
# Loop on head and tail and plot label by extrapolation
for tail, head in zip(tails, heads):
for i, (pt0, pt1) in enumerate([tail, head]):
kw, angle, loc = self._segment_to_text_specs(
pt0, pt1, lonlat)
if not getattr(self, loc+'_labels'):
continue
kw.update(label_style,
bbox={'pad': 0, 'visible': False})
text = formatter(tick_value)
if self.y_inline and lonlat == 'lat':
# 180 degrees isn't formatted with a
# suffix and adds confusion if it's inline
if abs(tick_value) == 180:
continue
x = x_midpoints[i]
y = tick_value
kw.update(clip_on=True)
y_set = True
else:
x = pt0[0]
y_set = False
if self.x_inline and lonlat == 'lon':
if abs(tick_value) == 180:
continue
x = tick_value
y = y_midpoints[i]
kw.update(clip_on=True)
elif not y_set:
y = pt0[1]
tt = self.axes.text(x, y, text, **kw)
tt._angle = angle
priority = (((lonlat == 'lon') and
loc in ('bottom', 'top')) or
((lonlat == 'lat') and
loc in ('left', 'right')))
self._labels.append((lonlat, priority, tt))
getattr(self, loc + '_label_artists').append(tt)
# Sort labels
if self._labels:
self._labels.sort(key=operator.itemgetter(0), reverse=True)
self._update_labels_visibility(renderer)
def _segment_to_text_specs(self, pt0, pt1, lonlat):
"""Get appropriate kwargs for a label from lon or lat line segment"""
x0, y0 = pt0
x1, y1 = pt1
angle = np.arctan2(y0-y1, x0-x1) * 180 / np.pi
kw, loc = self._segment_angle_to_text_specs(angle, lonlat)
return kw, angle, loc
def _text_angle_to_specs_(self, angle, lonlat):
"""Get specs for a rotated label from its angle in degrees"""
angle %= 360
if angle > 180:
angle -= 360
if ((self.x_inline and lonlat == 'lon') or
(self.y_inline and lonlat == 'lat')):
kw = {'rotation': 0, 'rotation_mode': 'anchor',
'ha': 'center', 'va': 'center'}
loc = 'bottom'
return kw, loc
# Default options
kw = {'rotation': angle, 'rotation_mode': 'anchor'}
# Options that depend in which quarter the angle falls
if abs(angle) <= 45:
loc = 'right'
kw.update(ha='left', va='center')
elif abs(angle) >= 135:
loc = 'left'
kw.update(ha='right', va='center')
kw['rotation'] -= np.sign(angle) * 180
elif angle > 45:
loc = 'top'
kw.update(ha='center', va='bottom', rotation=angle-90)
else:
loc = 'bottom'
kw.update(ha='center', va='top', rotation=angle+90)
return kw, loc
def _segment_angle_to_text_specs(self, angle, lonlat):
"""Get appropriate kwargs for a given text angle"""
kw, loc = self._text_angle_to_specs_(angle, lonlat)
if not self.rotate_labels:
angle = {'top': 90., 'right': 0.,
'bottom': -90., 'left': 180.}[loc]
del kw['rotation']
if ((self.x_inline and lonlat == 'lon') or
(self.y_inline and lonlat == 'lat')):
kw.update(transform=cartopy.crs.PlateCarree())
else:
xpadding = (self.xpadding if self.xpadding is not None
else matplotlib.rc_params['xtick.major.pad'])
ypadding = (self.ypadding if self.ypadding is not None
else matplotlib.rc_params['ytick.major.pad'])
dx = ypadding * np.cos(angle * np.pi / 180)
dy = xpadding * np.sin(angle * np.pi / 180)
transform = mtrans.offset_copy(
self.axes.transData, self.axes.figure,
x=dx, y=dy, units='dots')
kw.update(transform=transform)
return kw, loc
def _update_labels_visibility(self, renderer):
"""Update the visibility of each plotted label
The following rules apply:
- Labels are plotted and checked by order of priority,
with a high priority for longitude labels at the bottom and
top of the map, and the reverse for latitude labels.
- A label must not overlap another label marked as visible.
- A label must not overlap the map boundary.
- When a label is about to be hidden, other angles are tried in the
absolute given limit of max_delta_angle by increments of delta_angle
of difference from the original angle.
"""
if renderer is None or not self._labels:
return
paths = []
outline_path = None
delta_angle = 22.5
max_delta_angle = 45
axes_children = self.axes.get_children()
def remove_path_dupes(path):
"""
Remove duplicate points in a path (zero-length segments).
This is necessary only for Matplotlib 3.1.0 -- 3.1.2, because
Path.intersects_path incorrectly returns True for any paths with
such segments.
"""
segment_length = np.diff(path.vertices, axis=0)
mask = np.logical_or.reduce(segment_length != 0, axis=1)
mask = np.append(mask, True)
path = mpath.Path(np.compress(mask, path.vertices, axis=0),
np.compress(mask, path.codes, axis=0))
return path
for lonlat, priority, artist in self._labels:
if artist not in axes_children:
warnings.warn('The labels of this gridliner do not belong to '
'the gridliner axes')
orig_specs = {'rotation': artist.get_rotation(),
'ha': artist.get_ha(),
'va': artist.get_va()}
# Compute angles to try
angles = [None]
for abs_delta_angle in np.arange(delta_angle, max_delta_angle+1,
delta_angle):
angles.append(artist._angle + abs_delta_angle)
angles.append(artist._angle - abs_delta_angle)
# Loop on angles until it works
for angle in angles:
if ((self.x_inline and lonlat == 'lon') or
(self.y_inline and lonlat == 'lat')):
angle = 0
if angle is not None:
specs, _ = self._segment_angle_to_text_specs(angle, lonlat)
artist.update(specs)
artist.update_bbox_position_size(renderer)
this_patch = artist.get_bbox_patch()
this_path = this_patch.get_path().transformed(
this_patch.get_transform())
if '3.1.0' <= matplotlib.__version__ <= '3.1.2':
this_path = remove_path_dupes(this_path)
center = artist.get_transform().transform_point(
artist.get_position())
visible = False
for path in paths:
# Check it does not overlap another label
if this_path.intersects_path(path):
break
else:
# Finally check that it does not overlap the map
if outline_path is None:
outline_path = (self.axes.patch.get_path()
.transformed(self.axes.transData))
if '3.1.0' <= matplotlib.__version__ <= '3.1.2':
outline_path = remove_path_dupes(outline_path)
# Inline must be within the map.
if ((lonlat == 'lon' and self.x_inline) or
(lonlat == 'lat' and self.y_inline)):
# TODO: When Matplotlib clip path works on text, this
# clipping can be left to it.
if outline_path.contains_point(center):
visible = True
# Non-inline must not run through the outline.
elif not outline_path.intersects_path(this_path):
visible = True
# Good
if visible:
break
if ((self.x_inline and lonlat == 'lon') or
(self.y_inline and lonlat == 'lat')):
break
# Action
artist.set_visible(visible)
if not visible:
artist.update(orig_specs)
else:
paths.append(this_path)
def _assert_can_draw_ticks(self):
"""
Check to see if ticks can be drawn. Either returns True or raises
an exception.
"""
# Check labelling is supported, currently a limited set of options.
if not isinstance(self.crs, cartopy.crs.PlateCarree):
raise TypeError('Cannot label {crs.__class__.__name__} gridlines.'
' Only PlateCarree gridlines are currently '
'supported.'.format(crs=self.crs))
return True
def _axes_domain(self, nx=None, ny=None):
"""Return lon_range, lat_range"""
DEBUG = False
transform = self._crs_transform()
ax_transform = self.axes.transAxes
desired_trans = ax_transform - transform
nx = nx or 100
ny = ny or 100
x = np.linspace(1e-9, 1 - 1e-9, nx)
y = np.linspace(1e-9, 1 - 1e-9, ny)
x, y = np.meshgrid(x, y)
coords = np.column_stack((x.ravel(), y.ravel()))
in_data = desired_trans.transform(coords)
ax_to_bkg_patch = self.axes.transAxes - self.axes.patch.get_transform()
# convert the coordinates of the data to the background patches
# coordinates
background_coord = ax_to_bkg_patch.transform(coords)
ok = self.axes.patch.get_path().contains_points(background_coord)
if DEBUG:
import matplotlib.pyplot as plt
plt.plot(coords[ok, 0], coords[ok, 1], 'or',
clip_on=False, transform=ax_transform)
plt.plot(coords[~ok, 0], coords[~ok, 1], 'ob',
clip_on=False, transform=ax_transform)
inside = in_data[ok, :]
# If there were no data points in the axes we just use the x and y
# range of the projection.
if inside.size == 0:
lon_range = self.crs.x_limits
lat_range = self.crs.y_limits
else:
# np.isfinite must be used to prevent np.inf values that
# not filtered by np.nanmax for some projections
lat_max = np.compress(np.isfinite(inside[:, 1]),
inside[:, 1])
if lat_max.size == 0:
lon_range = self.crs.x_limits
lat_range = self.crs.y_limits
else:
lat_max = lat_max.max()
lon_range = np.nanmin(inside[:, 0]), np.nanmax(inside[:, 0])
lat_range = np.nanmin(inside[:, 1]), lat_max
# XXX Cartopy specific thing. Perhaps make this bit a specialisation
# in a subclass...
crs = self.crs
if isinstance(crs, Projection):
lon_range = np.clip(lon_range, *crs.x_limits)
lat_range = np.clip(lat_range, *crs.y_limits)
# if the limit is >90% of the full x limit, then just use the full
# x limit (this makes circular handling better)
prct = np.abs(np.diff(lon_range) / np.diff(crs.x_limits))
if prct > 0.9:
lon_range = crs.x_limits
return lon_range, lat_range
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